Cyclic Noise Removal in Borehole Imaging via Frequency Domain Filtering

Solution Overview

Problem

Conventional borehole imaging techniques suffer from cyclical or oscillating noise, which complicates the interpretation of borehole image data and makes it difficult to identify geological features and determine formation parameters accurately.

Innovation Solution

The method involves transforming borehole images into the frequency domain using a two-dimensional transform, identifying and removing cyclic noise components, and then inverse transforming them back into the spatial domain to obtain a corrected image, allowing for improved feature identification and parameter evaluation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional LWD imaging techniques are used, then borehole images can be obtained, but cyclical noise complicates the interpretation of borehole image data

Engineering Contradiction:

Improveimage qualityVSAvoidcyclical noise

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent extracts and removes cyclical noise components from borehole images by transforming the image into the frequency domain using a two-dimensional transform, identifying noise peaks, and eliminating them through filtering. The cleaned frequency domain data is then inverse transformed back to the spatial domain, resulting in a noise-reduced image that improves measurement precision while maintaining the harmful factor removal capability.

Inventive Principle:

Principle #2Taking out (Extraction)

2Difficulty of detecting and measuring

If cyclical noise is present in borehole images, then images can be acquired, but geological features become difficult to identify

Engineering Contradiction:

Improvegeological feature identificationVSAvoidgeological information

Core Design Contradiction:

Difficulty of detecting and measuringVSLoss of information

Solution Approach 1:

The patent converts the harmful cyclical noise into beneficial information by first transforming the noisy image into the frequency domain, where the noise appears as distinct peaks. By analyzing and removing these peaks, the process actually enhances the visibility of genuine geological features, turning the noise problem into an opportunity to improve feature detection accuracy.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

3Measurement precision

If conventional imaging techniques are used, then borehole images can be obtained, but formation parameters cannot be determined accurately

Engineering Contradiction:

Improveformation parameter determinationVSAvoidcyclical noise

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent extracts and removes cyclical noise components from borehole images by transforming the image into the frequency domain using a two-dimensional transform, identifying noise peaks, and eliminating them through filtering. The cleaned frequency domain data is then inverse transformed back to the spatial domain, resulting in a noise-reduced image that improves measurement precision while maintaining the harmful factor removal capability.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS8682102B2Cyclic noise removal in borehole imaging

Publication Date: 2014.03.25 SCHLUMBERGER TECH CORP

AI summary

A method for removing cyclic noise from a borehole image includes transforming the image into the frequency domain using a two-dimensional (2-D) transform (e.g., using a discrete cosine transform). The cyclic noise components (peaks) are removed from the transformed image which is then inverse transformed back into the spatial domain using an inverse 2-D transform to obtain a corrected image. An automated method enables the cyclic peaks to be identified and removed from the borehole image via downhole processing.